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1 PCE 2.1: The Co-Relationship of Containment and CFDs Gordon Johnson Senior CFD Manager at Subzero Engineering CDCDP (Certified Data Center Design Professional)

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Presentation on theme: "1 PCE 2.1: The Co-Relationship of Containment and CFDs Gordon Johnson Senior CFD Manager at Subzero Engineering CDCDP (Certified Data Center Design Professional)"— Presentation transcript:

1 1 PCE 2.1: The Co-Relationship of Containment and CFDs Gordon Johnson Senior CFD Manager at Subzero Engineering CDCDP (Certified Data Center Design Professional) DCEP (Data Center Energy Practitioner) BSEE from New Jersey Institute of Technology

2 2 Data Center World – Certified Vendor Neutral Each presenter is required to certify that their presentation will be vendor-neutral. As an attendee you have a right to enforce this policy of having no sales pitch within a session by alerting the speaker if you feel the session is not being presented in a vendor neutral fashion. If the issue continues to be a problem, please alert Data Center World staff after the session is complete.

3 3 The Co-Relationship of Containment & CFDs This session will address a range of airflow management solutions to a variety of data center floor plan and equipment layout challenges. Before-and- after energy consumption data will give data center operation managers a better idea of total cost of ownership based on a variety of real-life scenarios. Most importantly the relationship between effective CFDs and innovative containment designs will be presented.

4 4 The Co-Relationship of Containment & CFDs Computational Fluid Dynamics or CFDs provide a comprehensive approach to modeling data center airflow, giving the Data Center Energy Practitioner (DCEP) the ability to determine which best practices should be employed to ensure safe, yet economical thermal parameters of computer equipment. What do CFDs teach us about containment?

5 5 Separation of Supply and Return Airflow The most important development in data center cooling in the last 10 years has been the value of full separation of supply and return airflow.

6 6 Data Center Containment Data center containment is the physical separation of supply and return airflow by employing hot aisle containment, cold aisle containment, and/or a combination of both.

7 7 CFDs and Containment What are the key ways CFD engineering works with containment to increase cooling reliability & efficiency? Baseline CFD Cold aisle containment CFD Hot aisle containment CFD Containment w/ CRAC failure (N+1) Containment w/ reduced airflow (VFD fans) Containment ROI Containment thermal report

8 8 Goals of CFD Analysis Reduce/eliminate “hot spots”. (N + 1) cooling. Lower operational costs of data center (Save $$$). Allow for future growth (IT load). Use CFD to predict savings (ROI) by adding containment (cold or hot aisle) to data center.

9 9 Power Usage Effectiveness (PUE) is a metric used to determine the energy efficiency. Power Usage Effectiveness (PUE)

10 10 Power Usage Effectiveness (PUE) is a metric used to determine the energy efficiency. PUE = Total Facility Energy/Total IT Energy PUE Breakdown Data Center Power Utilization Power Usage Effectiveness (PUE)

11 11 RTI is a measure of net By-Pass or net Recirculation Air. It is the ratio of total equipment airflow to total air-handler airflow expressed as a %. RTI

12 12 RTI is a measure of net By-Pass or net Recirculation Air. It is the ratio of total equipment airflow to total air-handler airflow expressed as a %. 100% means balanced airflow <100% indicates net airflow By-pass >100% indicates net airflow Recirculation Return Temperature Index (RTI) = (Rack Flow Rate/Air Handler Flow Rate) x 100 Net By-Pass Air Target AirflowNet Recirculation Air RTI

13 13 RCI is a measure of compliance with ASHRAE air intake temperature guidelines and is expressed as a percentage with the maximum value being 100%. RCI (Rack Cooling Index)

14 14 RCI is a measure of compliance with ASHRAE air intake temperature guidelines and is expressed as a percentage with the maximum value being 100%. RCI (Rack Cooling Index) RCH HI is a measure of the absence of over-temperatures. 100% means no temperature is above maximum recommended. RCH LO is a measure of the absence of under-temperatures. 100% means no temperature is below minimum recommended.

15 15 CFD Models 1 Baseline model “as is”. 2 Baseline model with CRAC failure (N + 1). 3 Add cold aisle containment to model. 4 Raise SAT (Supply Air Temperature). 5 Lower VFD fan speed. 6 Analyze effect of CRAC failure (N + 1).

16 16 CFD MODELS

17 17 Data Center Description 4,976 sq. ft. raised floor 480 kW of IT load Heat Load Density 96.5 W/sq. ft. 8 Liebert CW084DCS CRACs (Liebert CW084DCS units), 12,100 CFM per unit, nominal sensible cooling at 24.1 Tons (84.7 kW). CRACs equipped with VFD/VSD (Variable Freq/Speed Drives), SATSP of CRACs @ 62 °F. Total cooling capacity with fans at full speed is 96,800 CFM. Total cooling demand @ 74,349 CFM (based on airflow giving a 20F temperature rise through the server, expressed by the following formula): Cooling airflow in CFM = 154 * (Heat load in kW)

18 18 Data Center Operating Cost “Estimate” IT Heat Load = 480 kW Assume PUE = 2 (typical) PUE = Total Facility Energy / Total IT Energy 2 = Total Facility Energy / 480 kW Total Facility Energy = 960 kW Assumed cost of Electricity = $ 0.10 / kW-hr 8760 hours per year Annual cost = 960 x.10 x 8760 = $840,960

19 19 Baseline CFD Model Floor Plan Subfloor Heat Load 480kW

20 20 Return Temperature Index (RTI) = (Rack Flow Rate/Air Handler Flow Rate) x 100 RTI = (74,349/96,800) x 100 = 76.8% Baseline CFD Model (Results)

21 21 Note: 2 Racks with Inlet Temps above the ASHRAE Allowable Range! 14 Racks with Inlet Temps above the ASHRAE Recommended Range Baseline CFD Model (Inlet Temps)

22 22 Baseline CFD Model (3D Inlet Temps)

23 23 (6’ Elevation) Baseline Model

24 24 91 Degree Hotspot! Baseline Model (3D Airflow)

25 25 Note: 9 Racks with Inlet Temps above the ASHRAE Allowable Range! 30 Racks with Inlet Temps above the ASHRAE Recommended Range Baseline CFD Model (CRAC Failure)

26 26 SHOULD I INSTALL CAC OR HAC?

27 27 Cold Aisle Containment A Cold Aisle Containment system (CAC) encloses the cold aisle, ensuring that only cold air flows into the air intakes of IT racks. By containing the cold aisle, the hot and cold air streams are separated.

28 28 Hot Aisle Containment A Hot Aisle Containment system (HAC) encloses the hot aisle to collect the IT equipment’s hot exhaust air, ensuring that the CRAC units only receive hot air from the aisles. By containing the hot aisle, the hot and cold air streams are separated.

29 29 Benefits of CAC or HAC Reduced Energy Consumption Increased Cooling Capacity Increased Rack Population Consistent Acceptable Supply across IT Intake More Power Available for IT Equipment Increased Equipment Up-Time Longer Hardware Life (MTBF)

30 30 More Benefits Containment allows for lower cooling unit fan speeds, higher chilled water temperature, decommissioning of redundant cooling units, and increased use of free cooling. According to the U.S. EPA, a robust containment solution can reduce fan energy consumption by up to 25% and deliver 20% savings at the cold water chiller. According to Data Center Knowledge’s Energy Efficiency Guide, containment can save a data center approximately 30% of its annual utility bill without additional CapEx (Capital Expenditures).

31 31 Return Temperature Index (RTI) = (Rack Flow Rate/Air Handler Flow Rate) x 100 RTI = (74,349/96,800) x 100 = 76.8% CAC Model (Results) Rack Flow Rate Air Handler Flow Rate No Hot Spots!

32 32 CAC Model (Inlet Temps)

33 33 CAC Model CRAC OFF (Results) No Hot Spots!

34 34 CAC Model CRAC OFF (Inlet Temps)

35 35 HAC Model (Results) No Hot Spots! Note: Same results as CAC, all hot spots eliminated from Data Center

36 36 HAC CFD Model (6’ Elevation)(Inlet Temps) (3D Floor Plan) (Drop Ceiling Airflow)

37 37 CFD Model Results (CAC and HAC) Elimination of hot spots. Cooling system can be set to a higher temperature (saving energy and increasing cooling capacity) and still supply the heat load with safe operating temperatures. Economizer hours (if used) are increased. Humidification/dehumidification costs are reduced. Allows for future IT growth in data center. Provides CRAC redundancy (N + 1).

38 38 CAC Model SATSP 72ºF (Results) No Hot Spots!

39 39 CAC Model SATSP 72ºF (Inlet Temps) (6’ Elevation)

40 40 Data Center Operating Savings IT Heat Load = 480 kW, Assume Baseline PUE = 2 Total Facility Energy = 960 kW Annual cost = 960 x.10 x 8760 = $840,960 Increase SATSP by 10 °F (2-4% overall savings per degree increase) $840,960 x 10 x.02 = $168,192

41 41 Data Center Operating Savings IT Heat Load = 480 kW, Assume Baseline PUE = 2 Total Facility Energy = 960 kW Annual cost = 960 x.10 x 8760 = $840,960 Increase SATSP by 10 °F (2-4% overall savings) $840,960 x.02 = $168,192 New Annual cost = $840,960 - $168,192 = $672,768 $672,768 = new Total Facility Energy x.10 x 8760 New Total Facility Energy = 768 kW New PUE = 768/480 = 1.6

42 42 Return Temperature Index (RTI) = (Rack Flow Rate/Air Handler Flow Rate) x 100 RTI = (74,349/77,400) x 100 = 96.1% CAC Model SATSP 72ºF, VFDs @ 80% (Results) Rack Flow Rate Air Handler Flow Rate No Hot Spots!

43 43 CAC Model SATSP 72ºF, VFDs @ 80% (Inlet Temps) (6’ Elevation)

44 44 CRAC Savings From Reducing Fan Speed Fan Affinity Law: (kW 1 /kW 2 ) = (CFM 1 /CFM 2 ) 3 7.5kW/kW 2 = (12,100/9,680) 3 kW 2 = 3.84 kW = Fan Power @ 80% speed

45 45 CRAC Savings kW 2 = 3.84 kW = Fan Power @ 80% speed 7.5 kW – 3.84 kW = 3.66 kW saved 3.66 kW x 8 CRACs x.1 x 8760 = $25,649 Additional yearly savings = $25,649 Note: A reduction in fan speed will also effect the energy consumed in producing the chilled water.

46 46 Updated Data Center Operating Savings New Annual cost = $840,960 - $168,192 - $25,649 = $647,119 $647,119 = new Total Facility Energy x.10 x 8760 New Total Facility Energy = 739 kW New PUE = 739/480 = 1.5

47 47 CASE STUDY

48 48 Data Center Description Data Center is a raised floor design of 9,042 sq ft, 405 kW of IT load, and no drop ceiling. Customer wanted to increase IT load to 602 kW. Current Heat Load Density 44.8 W/sq ft (to 66.6 W/sq ft). 11 CRACs (Liebert DH240G units), each with airflow rate at 11,000 CFM and nominal sensible cooling at 19.8 Tons (69.7 kW). CRACs are not equipped with VFD/VSD fans. Total cooling capacity @ 121,000 CFM, total cooling demand @ 63,808 CFM (RTI = 53%). 65 Racks with Inlet Temps > 80.6°F

49 49 Hot Spots! Baseline CFD Model (Results)

50 50 Baseline CFD Model (3D Floor Plan) (Inlet Temps) (6’ Elev.)

51 51 No Hot Spots! CAC Results

52 52 Case Study #1 CAC (3D Floor Plan) (Inlet Temps) (6’ Elev.)

53 53 CAC Results Data Center raised IT load 33%. 0 Racks with Inlet Temps > 80.6°F. Reduced airflow (turned OFF unnecessary CRAC units), increased temperature set points in data center (RTI = 86%). NYSERDA (New York State Energy Research and Development Authority) covered substantial cost of containment installation. CFD models estimated yearly savings of $150,409 and ROI of 1.56 years (excluding energy rebates).

54 54 Customer Comments https://www.nyi.net/media/more/nyi_rolls_out_new_cold_aisle_containment_system_within_data_centers

55 55 CFD ENGINEERING CONTAINMENT Innovative thermal solutions for the data center

56 56 3 Key Things You Have Learned During this Session 1.CFDs quantify the benefits of containment 2.Return on investment calculations are better made with a CFD study 3.Containment benefits are both diverse and all encompassing in any cooling solution

57 57 Q & A

58 58 Thank you Gordon Johnson Senior CFD Manager at Subzero Engineering CDCDP (Certified Data Center Design Professional) DCEP (Data Center Energy Practitioner) BSEE from New Jersey Institute of Technology GordonJohnson@subzeroeng.com 801.810.3500 x 559


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